Towards sustainability in the adoption of sustainable agricultural practices: Implications on household poverty, food and nutrition security

Mgomezulu, Wisdom Richard; Edriss, Abdi-Khalil; Machira, Kennedy; Pangapanga-Phiri, Innocent

doi:10.1016/j.igd.2023.100054

Cited by 15 publications

(5 citation statements)

References 17 publications

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“…Different results were concluded by research (Broussard, 2019;Kassie et al, 2014) that the gender of the household head greatly determines the status of food insecurity where female household heads tend to be food insecure compared to men. Another study (Mgomezulu et al, 2023) concluded differently that the gender of the head of the household and the number of household members did not significantly affect household food security.…”

Section: Interpretation Of Ordinal Regression Equationsmentioning

confidence: 95%

Cigarette Consumption, Credit Access, and Determinants Household Food Security in Lampung Province

Lestari,

Gunarto,

Yuliawan

2023

JSEP

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The SDGs emphasize the need to end hunger, improve nutrition and achieve food security. Meeting food needs occurs when everyone has physical and economic access to sufficient, safe and nutritious food. Lampung Province is a province that is a production center for rice, cassava, and corn. This shows that there is the ability of Lampung Province to provide food for its inhabitants. However, regional food availability at the macro level does not guarantee household food security at the micro level. This study uses Susenas raw data for Lampung Province in 2022. Food security status is measured based on a combination of the share of food expenditure and the level of energy consumption which adopts the Jonsson and Toole (1991) indicators to see the effect of several household variables. This study uses ordinal logit regression where the categorization of status is divided into four, namely food insecurity, food deprivation, food vulnerable, and food security. As much as 41,54 percent of households are food secure and 9,5 percent are food insecure. Based on ordinal logit regression analysis, the researchers concluded that the variables affecting household food security in Lampung Province were cigarette consumption, access to credit, social assistance, land assets, internet use, place of residence, income, number of household members, whether the household works on agriculture or not, and age head household.

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Section: Interpretation Of Ordinal Regression Equationsmentioning

confidence: 95%

Cigarette Consumption, Credit Access, and Determinants Household Food Security in Lampung Province

Lestari,

Gunarto,

Yuliawan

2023

JSEP

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“…Tan et al (2022) found a significant peer effect in promoting corporate green innovation after the implementation of green credit policies, which mainly stems from more investment in clean projects and credit restrictions on polluting projects. Aside from green credit policies, the development of green finance also has a significant impact on green innovation (Li et al, 2023a;Mgomezulu et al, 2023;Li et al, 2023b;Raihan, 2023;Zhongzheng, 2023;Ahuja et al, 2023;Yang and Chen, 2023;Awan and Yaqoob, 2023;Yolcan, 2023). explored the effect of green finance on green total factor productivity by introducing a system of green credit, securities, insurance, and investment indicators, noting that the development of green finance has a significantly positive impact on green technological progress in provinces of China having low environmental protection and high pollution levels.…”

Section: Literature Reviewmentioning

confidence: 99%

The impact of political competition on green innovation: A new insight into sustainable development

Yang

Guo

Gong

et al. 2023

Sustainable Development

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This research examines a panel of 121 economies worldwide over the period 1980–2020 for the impact of political competition on green innovation. We find that an increase in the intensity of political competition has a significantly negative impact on green innovation and that this impact remains significant in the long term, especially for non‐OECD countries and middle (low) income countries, whereas the sub‐indicators of political competition indicate that the level of institutionalization of political participation and the degree of government restrictions on political participation have different impacts on green innovation. The findings also reveal that lower political risk and higher levels of globalization positively moderate the negative impact of political competition on green innovation. The adverse effects of party competition are exacerbated when left‐wing parties are in power. This study offers new insight into sustainable development based on examining the relationship between political competition and green innovation.

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“…It can be seen from the number of times the phrases are extracted: (1) The current research hotspots of smart agriculture are the IoT, climate change, machine learning, precision agriculture, wireless sensor networks, soil moisture, deep learning, artificial intelligence, big data and food security. (2) Classic research areas such as agricultural production and crop yield are receiving less attention [39]. (3) New research areas similar to unmanned aerial and image processing have received less attention from scholars than expected [38,39].…”

Section: Smart Agriculturementioning

confidence: 99%

“…(2) Classic research areas such as agricultural production and crop yield are receiving less attention [39]. (3) New research areas similar to unmanned aerial and image processing have received less attention from scholars than expected [38,39].…”

Section: Smart Agriculturementioning

confidence: 99%

Bibliometric Analysis of Trends in Smart Irrigation for Smart Agriculture

Pang,

Marinello,

Tang

et al. 2023

Sustainability

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Agriculture is considered one of the most critical sectors that play a strategic role in ensuring food security. It is directly related to human development and social stability. The agricultural sector is currently incorporating new technologies from other areas. These phenomena are smart agriculture and smart irrigation. However, a challenge to research is the integration of technologies from different knowledge fields, which has caused theoretical and practical difficulties. Thus, our purpose in this study has been to understand the core of these two themes. We extracted publications in Scopus and used bibliometric methods for high-frequency word and phrase analysis. Research shows that current research on smart agriculture mainly focuses on the Internet of Things, climate change, machine learning, precision agriculture and wireless sensor networks. Simultaneously, the Internet of Things, irrigation systems, soil moisture, wireless sensor networks and climate change have received the most scholarly attention in smart irrigation. This study used cluster analysis to find that the IoT has the most apparent growth rate in smart agriculture and smart irrigation, with five-year growth rates of 1617% and 2285%, respectively. In addition, machine learning, deep learning and neural networks have enormous potential in smart irrigation compared with smart agriculture.

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Towards sustainability in the adoption of sustainable agricultural practices: Implications on household poverty, food and nutrition security

Cited by 15 publications

References 17 publications

Cigarette Consumption, Credit Access, and Determinants Household Food Security in Lampung Province

Cigarette Consumption, Credit Access, and Determinants Household Food Security in Lampung Province

The impact of political competition on green innovation: A new insight into sustainable development

Bibliometric Analysis of Trends in Smart Irrigation for Smart Agriculture

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